3 accepted papers
We propose a multimodal integration framework to enhance the precision of Vision-Language-Action (VLA) models in contact-rich robotic tasks. Although visual perception is essential for task grounding, it often lacks the force awareness required for high-precision alignment and insertion. To address …
"This paper aims to adapt the source model to the target environment, leveraging small user feedback (, labeled target data) readily available in real-world applications. We find that existing semi-supervised domain adaptation (SemiSDA) methods often suffer from poorly improved adaptation performanc…
In this paper, we propose a novel learning-based polygonal point set tracking method. Compared to existing video object segmentation (VOS) methods that propagate pixel-wise object mask information, we propagate a polygonal point set over frames. Specifically, the set is defined as a subset of points…